{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "508a5f1d",
   "metadata": {},
   "source": [
    "# Install and import dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ba350a0f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting torch\n",
      "  Using cached torch-1.11.0-cp38-none-macosx_10_9_x86_64.whl (129.9 MB)\n",
      "Collecting torchvision\n",
      "  Using cached torchvision-0.12.0-cp38-cp38-macosx_10_9_x86_64.whl (1.3 MB)\n",
      "Collecting torchaudio\n",
      "  Using cached torchaudio-0.11.0-cp38-cp38-macosx_10_15_x86_64.whl (2.4 MB)\n",
      "Collecting typing-extensions\n",
      "  Using cached typing_extensions-4.2.0-py3-none-any.whl (24 kB)\n",
      "Collecting pillow!=8.3.*,>=5.3.0\n",
      "  Using cached Pillow-9.1.0-cp38-cp38-macosx_10_9_x86_64.whl (3.1 MB)\n",
      "Collecting numpy\n",
      "  Using cached numpy-1.22.3-cp38-cp38-macosx_10_14_x86_64.whl (17.6 MB)\n",
      "Collecting requests\n",
      "  Using cached requests-2.27.1-py2.py3-none-any.whl (63 kB)\n",
      "Collecting idna<4,>=2.5; python_version >= \"3\"\n",
      "  Using cached idna-3.3-py3-none-any.whl (61 kB)\n",
      "Collecting urllib3<1.27,>=1.21.1\n",
      "  Using cached urllib3-1.26.9-py2.py3-none-any.whl (138 kB)\n",
      "Collecting certifi>=2017.4.17\n",
      "  Using cached certifi-2021.10.8-py2.py3-none-any.whl (149 kB)\n",
      "Collecting charset-normalizer~=2.0.0; python_version >= \"3\"\n",
      "  Using cached charset_normalizer-2.0.12-py3-none-any.whl (39 kB)\n",
      "Installing collected packages: typing-extensions, torch, pillow, numpy, idna, urllib3, certifi, charset-normalizer, requests, torchvision, torchaudio\n",
      "Successfully installed certifi-2021.10.8 charset-normalizer-2.0.12 idna-3.3 numpy-1.22.3 pillow-9.1.0 requests-2.27.1 torch-1.11.0 torchaudio-0.11.0 torchvision-0.12.0 typing-extensions-4.2.0 urllib3-1.26.9\n",
      "\u001b[33mWARNING: You are using pip version 20.2.3; however, version 22.0.4 is available.\n",
      "You should consider upgrading via the '/Users/sanjeev/Documents/yolo/yolo/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip3 install torch torchvision torchaudio #installing pytorch\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "177f8ab6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cloning into 'yolov5'...\n",
      "remote: Enumerating objects: 13329, done.\u001b[K\n",
      "remote: Counting objects: 100% (43/43), done.\u001b[K\n",
      "remote: Compressing objects: 100% (14/14), done.\u001b[K\n",
      "remote: Total 13329 (delta 30), reused 39 (delta 29), pack-reused 13286\u001b[K\n",
      "Receiving objects: 100% (13329/13329), 12.05 MiB | 10.56 MiB/s, done.\n",
      "Resolving deltas: 100% (9280/9280), done.\n"
     ]
    }
   ],
   "source": [
    "!git clone https://github.com/ultralytics/yolov5  # cloning yolov5 \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c88436cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/sanjeev/Documents/yolo/yolov5\n"
     ]
    }
   ],
   "source": [
    "cd yolov5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2e24e792",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting matplotlib>=3.2.2\n",
      "  Using cached matplotlib-3.5.2-cp38-cp38-macosx_10_9_x86_64.whl (7.3 MB)\n",
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      "  Using cached opencv_python-4.5.5.64-cp36-abi3-macosx_10_15_x86_64.whl (46.3 MB)\n",
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      "Collecting PyYAML>=5.3.1\n",
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      "  Downloading scipy-1.8.0-cp38-cp38-macosx_10_9_x86_64.whl (34.8 MB)\n",
      "\u001b[K     |████████████████████████████████| 34.8 MB 205 kB/s  eta 0:00:01\n",
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      "\u001b[K     |████████████████████████████████| 292 kB 12.0 MB/s eta 0:00:01\n",
      "\u001b[?25hCollecting thop\n",
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      "Collecting cycler>=0.10\n",
      "  Using cached cycler-0.11.0-py3-none-any.whl (6.4 kB)\n",
      "Collecting kiwisolver>=1.0.1\n",
      "  Using cached kiwisolver-1.4.2-cp38-cp38-macosx_10_9_x86_64.whl (65 kB)\n",
      "Requirement already satisfied: packaging>=20.0 in /Users/sanjeev/Documents/yolo/yolo/lib/python3.8/site-packages (from matplotlib>=3.2.2->-r requirements.txt (line 4)) (21.3)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /Users/sanjeev/Documents/yolo/yolo/lib/python3.8/site-packages (from matplotlib>=3.2.2->-r requirements.txt (line 4)) (3.0.9)\n",
      "Collecting fonttools>=4.22.0\n",
      "  Using cached fonttools-4.33.3-py3-none-any.whl (930 kB)\n",
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      "Requirement already satisfied: idna<4,>=2.5; python_version >= \"3\" in /Users/sanjeev/Documents/yolo/yolo/lib/python3.8/site-packages (from requests>=2.23.0->-r requirements.txt (line 9)) (3.3)\n",
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      "\u001b[?25hCollecting protobuf>=3.9.2\n",
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      "Requirement already satisfied: six>=1.5 in /Users/sanjeev/Documents/yolo/yolo/lib/python3.8/site-packages (from python-dateutil>=2.7->matplotlib>=3.2.2->-r requirements.txt (line 4)) (1.16.0)\n",
      "Collecting rsa<5,>=3.1.4; python_version >= \"3.6\"\n",
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      "Collecting zipp>=0.5\n",
      "  Using cached zipp-3.8.0-py3-none-any.whl (5.4 kB)\n",
      "Installing collected packages: cycler, kiwisolver, fonttools, matplotlib, opencv-python, PyYAML, scipy, tqdm, absl-py, pyasn1, rsa, cachetools, pyasn1-modules, google-auth, oauthlib, requests-oauthlib, google-auth-oauthlib, zipp, importlib-metadata, markdown, grpcio, protobuf, tensorboard-plugin-wit, wheel, werkzeug, tensorboard-data-server, tensorboard, pytz, pandas, seaborn, thop\n",
      "Successfully installed PyYAML-6.0 absl-py-1.0.0 cachetools-5.0.0 cycler-0.11.0 fonttools-4.33.3 google-auth-2.6.6 google-auth-oauthlib-0.4.6 grpcio-1.46.1 importlib-metadata-4.11.3 kiwisolver-1.4.2 markdown-3.3.7 matplotlib-3.5.2 oauthlib-3.2.0 opencv-python-4.5.5.64 pandas-1.4.2 protobuf-3.20.1 pyasn1-0.4.8 pyasn1-modules-0.2.8 pytz-2022.1 requests-oauthlib-1.3.1 rsa-4.8 scipy-1.8.0 seaborn-0.11.2 tensorboard-2.9.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 thop-0.0.31.post2005241907 tqdm-4.64.0 werkzeug-2.1.2 wheel-0.37.1 zipp-3.8.0\n",
      "\u001b[33mWARNING: You are using pip version 20.2.3; however, version 22.0.4 is available.\n",
      "You should consider upgrading via the '/Users/sanjeev/Documents/yolo/yolo/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install -r requirements.txt #installing the requirements for yolov5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e7b82530",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/sanjeev/Documents/yolo'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1f7e69f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting ipywidgets\n",
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      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in ./yolo/lib/python3.8/site-packages (from packaging->ipykernel>=4.5.1->ipywidgets) (3.0.9)\n",
      "Collecting importlib-resources>=1.4.0; python_version < \"3.9\"\n",
      "  Using cached importlib_resources-5.7.1-py3-none-any.whl (28 kB)\n",
      "Processing /Users/sanjeev/Library/Caches/pip/wheels/30/87/4f/6ac908945dc671cfe494bbb1b0374a5f81238e2d67936a397b/pyrsistent-0.18.1-cp38-cp38-macosx_10_9_x86_64.whl\n",
      "Collecting attrs>=17.4.0\n",
      "  Using cached attrs-21.4.0-py2.py3-none-any.whl (60 kB)\n",
      "Requirement already satisfied: six in ./yolo/lib/python3.8/site-packages (from asttokens->stack-data->ipython>=4.0.0; python_version >= \"3.3\"->ipywidgets) (1.16.0)\n",
      "Collecting MarkupSafe>=2.0\n",
      "  Using cached MarkupSafe-2.1.1-cp38-cp38-macosx_10_9_x86_64.whl (13 kB)\n",
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      "  Using cached argon2_cffi_bindings-21.2.0-cp36-abi3-macosx_10_9_x86_64.whl (29 kB)\n",
      "Collecting beautifulsoup4\n",
      "  Using cached beautifulsoup4-4.11.1-py3-none-any.whl (128 kB)\n",
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      "  Using cached jupyterlab_pygments-0.2.2-py2.py3-none-any.whl (21 kB)\n",
      "Collecting mistune<2,>=0.8.1\n",
      "  Using cached mistune-0.8.4-py2.py3-none-any.whl (16 kB)\n",
      "Collecting nbclient>=0.5.0\n",
      "  Downloading nbclient-0.6.3-py3-none-any.whl (71 kB)\n",
      "\u001b[K     |████████████████████████████████| 71 kB 2.4 MB/s eta 0:00:011\n",
      "\u001b[?25hCollecting tinycss2\n",
      "  Using cached tinycss2-1.1.1-py3-none-any.whl (21 kB)\n",
      "Collecting pandocfilters>=1.4.1\n",
      "  Using cached pandocfilters-1.5.0-py2.py3-none-any.whl (8.7 kB)\n",
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      "  Using cached defusedxml-0.7.1-py2.py3-none-any.whl (25 kB)\n",
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      "  Using cached bleach-5.0.0-py3-none-any.whl (160 kB)\n",
      "Requirement already satisfied: zipp>=3.1.0; python_version < \"3.10\" in ./yolo/lib/python3.8/site-packages (from importlib-resources>=1.4.0; python_version < \"3.9\"->jsonschema>=2.6->nbformat>=4.2.0->ipywidgets) (3.8.0)\n",
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      "  Using cached cffi-1.15.0-cp38-cp38-macosx_10_9_x86_64.whl (178 kB)\n",
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      "  Using cached pycparser-2.21-py2.py3-none-any.whl (118 kB)\n",
      "Installing collected packages: prometheus-client, MarkupSafe, jinja2, ipython-genutils, pycparser, cffi, argon2-cffi-bindings, argon2-cffi, Send2Trash, fastjsonschema, importlib-resources, pyrsistent, attrs, jsonschema, nbformat, terminado, soupsieve, beautifulsoup4, jupyterlab-pygments, mistune, nbclient, webencodings, tinycss2, pandocfilters, defusedxml, bleach, nbconvert, notebook, widgetsnbextension, jupyterlab-widgets, ipywidgets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successfully installed MarkupSafe-2.1.1 Send2Trash-1.8.0 argon2-cffi-21.3.0 argon2-cffi-bindings-21.2.0 attrs-21.4.0 beautifulsoup4-4.11.1 bleach-5.0.0 cffi-1.15.0 defusedxml-0.7.1 fastjsonschema-2.15.3 importlib-resources-5.7.1 ipython-genutils-0.2.0 ipywidgets-7.7.0 jinja2-3.1.2 jsonschema-4.5.1 jupyterlab-pygments-0.2.2 jupyterlab-widgets-1.1.0 mistune-0.8.4 nbclient-0.6.3 nbconvert-6.5.0 nbformat-5.4.0 notebook-6.4.11 pandocfilters-1.5.0 prometheus-client-0.14.1 pycparser-2.21 pyrsistent-0.18.1 soupsieve-2.3.2.post1 terminado-0.13.3 tinycss2-1.1.1 webencodings-0.5.1 widgetsnbextension-3.6.0\n",
      "\u001b[33mWARNING: You are using pip version 20.2.3; however, version 22.0.4 is available.\n",
      "You should consider upgrading via the '/Users/sanjeev/Documents/yolo/yolo/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install ipywidgets \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4c4b7ec7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch #importing pytorch\n",
    "from matplotlib import pyplot as plt \n",
    "import numpy as np\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88d99462",
   "metadata": {},
   "source": [
    "# Load model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8237d2f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using cache found in /Users/sanjeev/.cache/torch/hub/ultralytics_yolov5_master\n",
      "YOLOv5 🚀 2022-5-12 torch 1.11.0 CPU\n",
      "\n",
      "Fusing layers... \n",
      "YOLOv5s summary: 213 layers, 7225885 parameters, 0 gradients\n",
      "Adding AutoShape... \n"
     ]
    }
   ],
   "source": [
    "model = torch.hub.load('ultralytics/yolov5', 'yolov5s') #loading yolov5s(s = small) model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "52021499",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AutoShape(\n",
       "  (model): DetectMultiBackend(\n",
       "    (model): Model(\n",
       "      (model): Sequential(\n",
       "        (0): Conv(\n",
       "          (conv): Conv2d(3, 32, kernel_size=(6, 6), stride=(2, 2), padding=(2, 2))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (1): Conv(\n",
       "          (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (2): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (3): Conv(\n",
       "          (conv): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (4): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "            (1): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (5): Conv(\n",
       "          (conv): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (6): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "            (1): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "            (2): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (7): Conv(\n",
       "          (conv): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (8): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (9): SPPF(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): MaxPool2d(kernel_size=5, stride=1, padding=2, dilation=1, ceil_mode=False)\n",
       "        )\n",
       "        (10): Conv(\n",
       "          (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (11): Upsample(scale_factor=2.0, mode=nearest)\n",
       "        (12): Concat()\n",
       "        (13): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (14): Conv(\n",
       "          (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (15): Upsample(scale_factor=2.0, mode=nearest)\n",
       "        (16): Concat()\n",
       "        (17): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (18): Conv(\n",
       "          (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (19): Concat()\n",
       "        (20): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (21): Conv(\n",
       "          (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (22): Concat()\n",
       "        (23): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (24): Detect(\n",
       "          (m): ModuleList(\n",
       "            (0): Conv2d(128, 255, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (1): Conv2d(256, 255, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (2): Conv2d(512, 255, kernel_size=(1, 1), stride=(1, 1))\n",
       "          )\n",
       "        )\n",
       "      )\n",
       "    )\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1990f0c3",
   "metadata": {},
   "source": [
    "# Make detections with images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a009948",
   "metadata": {},
   "outputs": [],
   "source": [
    "img=['https://cdn.vox-cdn.com/thumbor/SLAqByY-1IyAnbvJpxug9I0JZNY=/232x0:2999x2075/920x613/filters:focal(232x0:2999x2075):format(webp)/cdn.vox-cdn.com/uploads/chorus_image/image/44219366/72499026.0.0.jpg']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "88ac24ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = model(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5d01d56c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "image 1/1: 613x920 21 cars, 2 trucks\n",
      "Speed: 1786.6ms pre-process, 392.7ms inference, 27.8ms NMS per image at shape (1, 3, 448, 640)\n"
     ]
    }
   ],
   "source": [
    "results.print()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "75c579ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.imshow(np.squeeze(results.render()))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "643d830c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>xmin</th>\n",
       "      <th>ymin</th>\n",
       "      <th>xmax</th>\n",
       "      <th>ymax</th>\n",
       "      <th>confidence</th>\n",
       "      <th>class</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>820.022949</td>\n",
       "      <td>497.076141</td>\n",
       "      <td>919.913391</td>\n",
       "      <td>612.890259</td>\n",
       "      <td>0.885624</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>479.530579</td>\n",
       "      <td>331.741577</td>\n",
       "      <td>573.064758</td>\n",
       "      <td>403.631805</td>\n",
       "      <td>0.876746</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>710.469055</td>\n",
       "      <td>425.512238</td>\n",
       "      <td>852.556885</td>\n",
       "      <td>521.895081</td>\n",
       "      <td>0.876550</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>510.959747</td>\n",
       "      <td>435.880463</td>\n",
       "      <td>643.002747</td>\n",
       "      <td>553.706482</td>\n",
       "      <td>0.843626</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>839.575195</td>\n",
       "      <td>383.353394</td>\n",
       "      <td>919.883179</td>\n",
       "      <td>466.531952</td>\n",
       "      <td>0.840771</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>447.064209</td>\n",
       "      <td>273.249451</td>\n",
       "      <td>515.892334</td>\n",
       "      <td>330.675385</td>\n",
       "      <td>0.823502</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>648.848938</td>\n",
       "      <td>348.478394</td>\n",
       "      <td>756.638367</td>\n",
       "      <td>423.739166</td>\n",
       "      <td>0.812843</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>777.415344</td>\n",
       "      <td>333.873047</td>\n",
       "      <td>887.311768</td>\n",
       "      <td>409.194702</td>\n",
       "      <td>0.802299</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>544.106445</td>\n",
       "      <td>118.119370</td>\n",
       "      <td>643.273865</td>\n",
       "      <td>223.274109</td>\n",
       "      <td>0.795985</td>\n",
       "      <td>7</td>\n",
       "      <td>truck</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>580.161072</td>\n",
       "      <td>285.044525</td>\n",
       "      <td>657.036865</td>\n",
       "      <td>344.084900</td>\n",
       "      <td>0.778562</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>57.845943</td>\n",
       "      <td>137.450226</td>\n",
       "      <td>95.456604</td>\n",
       "      <td>163.199890</td>\n",
       "      <td>0.777378</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>518.440491</td>\n",
       "      <td>207.645966</td>\n",
       "      <td>575.815979</td>\n",
       "      <td>245.147171</td>\n",
       "      <td>0.724364</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>628.990906</td>\n",
       "      <td>228.170212</td>\n",
       "      <td>690.291199</td>\n",
       "      <td>269.438538</td>\n",
       "      <td>0.720676</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>691.453430</td>\n",
       "      <td>262.459961</td>\n",
       "      <td>772.962097</td>\n",
       "      <td>315.044495</td>\n",
       "      <td>0.648238</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>725.870239</td>\n",
       "      <td>298.705841</td>\n",
       "      <td>812.114502</td>\n",
       "      <td>356.931335</td>\n",
       "      <td>0.631540</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>805.694153</td>\n",
       "      <td>256.422424</td>\n",
       "      <td>910.929077</td>\n",
       "      <td>326.257538</td>\n",
       "      <td>0.625695</td>\n",
       "      <td>7</td>\n",
       "      <td>truck</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>418.642517</td>\n",
       "      <td>191.365494</td>\n",
       "      <td>467.763550</td>\n",
       "      <td>235.354584</td>\n",
       "      <td>0.565941</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>440.102661</td>\n",
       "      <td>216.405823</td>\n",
       "      <td>498.658783</td>\n",
       "      <td>276.240234</td>\n",
       "      <td>0.468635</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>505.859467</td>\n",
       "      <td>195.517288</td>\n",
       "      <td>567.469055</td>\n",
       "      <td>237.375916</td>\n",
       "      <td>0.440276</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>491.023254</td>\n",
       "      <td>181.077362</td>\n",
       "      <td>545.124329</td>\n",
       "      <td>224.692276</td>\n",
       "      <td>0.392868</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>394.009857</td>\n",
       "      <td>146.865906</td>\n",
       "      <td>435.912384</td>\n",
       "      <td>178.482895</td>\n",
       "      <td>0.342168</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>408.454437</td>\n",
       "      <td>173.627060</td>\n",
       "      <td>446.646606</td>\n",
       "      <td>204.658951</td>\n",
       "      <td>0.335847</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>598.267395</td>\n",
       "      <td>199.848755</td>\n",
       "      <td>655.111206</td>\n",
       "      <td>242.004425</td>\n",
       "      <td>0.282282</td>\n",
       "      <td>2</td>\n",
       "      <td>car</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          xmin        ymin        xmax        ymax  confidence  class   name\n",
       "0   820.022949  497.076141  919.913391  612.890259    0.885624      2    car\n",
       "1   479.530579  331.741577  573.064758  403.631805    0.876746      2    car\n",
       "2   710.469055  425.512238  852.556885  521.895081    0.876550      2    car\n",
       "3   510.959747  435.880463  643.002747  553.706482    0.843626      2    car\n",
       "4   839.575195  383.353394  919.883179  466.531952    0.840771      2    car\n",
       "5   447.064209  273.249451  515.892334  330.675385    0.823502      2    car\n",
       "6   648.848938  348.478394  756.638367  423.739166    0.812843      2    car\n",
       "7   777.415344  333.873047  887.311768  409.194702    0.802299      2    car\n",
       "8   544.106445  118.119370  643.273865  223.274109    0.795985      7  truck\n",
       "9   580.161072  285.044525  657.036865  344.084900    0.778562      2    car\n",
       "10   57.845943  137.450226   95.456604  163.199890    0.777378      2    car\n",
       "11  518.440491  207.645966  575.815979  245.147171    0.724364      2    car\n",
       "12  628.990906  228.170212  690.291199  269.438538    0.720676      2    car\n",
       "13  691.453430  262.459961  772.962097  315.044495    0.648238      2    car\n",
       "14  725.870239  298.705841  812.114502  356.931335    0.631540      2    car\n",
       "15  805.694153  256.422424  910.929077  326.257538    0.625695      7  truck\n",
       "16  418.642517  191.365494  467.763550  235.354584    0.565941      2    car\n",
       "17  440.102661  216.405823  498.658783  276.240234    0.468635      2    car\n",
       "18  505.859467  195.517288  567.469055  237.375916    0.440276      2    car\n",
       "19  491.023254  181.077362  545.124329  224.692276    0.392868      2    car\n",
       "20  394.009857  146.865906  435.912384  178.482895    0.342168      2    car\n",
       "21  408.454437  173.627060  446.646606  204.658951    0.335847      2    car\n",
       "22  598.267395  199.848755  655.111206  242.004425    0.282282      2    car"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.pandas().xyxy[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "413d126c",
   "metadata": {},
   "source": [
    "# Real time detections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5a3aea8",
   "metadata": {},
   "outputs": [],
   "source": [
    "cap = cv2.VideoCapture(0)\n",
    "while cap.isOpened():\n",
    "    ret,frame = cap.read()\n",
    "    \n",
    "    #make detections\n",
    "    results = model(frame)\n",
    "    \n",
    "    cv2.imshow('YOLO',np.squeeze(results.render()))\n",
    "    \n",
    "    if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db453e5e",
   "metadata": {},
   "source": [
    "# Train from scratch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0ddc1816",
   "metadata": {},
   "outputs": [],
   "source": [
    "import uuid #unique identifier\n",
    "import os\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "254986aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "IMAGES_PATH = os.path.join('data','images')\n",
    "labels = ['awake','drowsy']\n",
    "number_imgs = 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7de932cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "collecting images for awake\n",
      "collecting images for awake, image number0\n",
      "collecting images for awake, image number1\n",
      "collecting images for awake, image number2\n",
      "collecting images for awake, image number3\n",
      "collecting images for awake, image number4\n",
      "collecting images for awake, image number5\n",
      "collecting images for awake, image number6\n",
      "collecting images for awake, image number7\n",
      "collecting images for awake, image number8\n",
      "collecting images for awake, image number9\n",
      "collecting images for awake, image number10\n",
      "collecting images for awake, image number11\n",
      "collecting images for awake, image number12\n",
      "collecting images for awake, image number13\n",
      "collecting images for awake, image number14\n",
      "collecting images for awake, image number15\n",
      "collecting images for awake, image number16\n",
      "collecting images for awake, image number17\n",
      "collecting images for awake, image number18\n",
      "collecting images for awake, image number19\n",
      "collecting images for drowsy\n",
      "collecting images for drowsy, image number0\n",
      "collecting images for drowsy, image number1\n",
      "collecting images for drowsy, image number2\n",
      "collecting images for drowsy, image number3\n",
      "collecting images for drowsy, image number4\n",
      "collecting images for drowsy, image number5\n",
      "collecting images for drowsy, image number6\n",
      "collecting images for drowsy, image number7\n",
      "collecting images for drowsy, image number8\n",
      "collecting images for drowsy, image number9\n",
      "collecting images for drowsy, image number10\n",
      "collecting images for drowsy, image number11\n",
      "collecting images for drowsy, image number12\n",
      "collecting images for drowsy, image number13\n",
      "collecting images for drowsy, image number14\n",
      "collecting images for drowsy, image number15\n",
      "collecting images for drowsy, image number16\n",
      "collecting images for drowsy, image number17\n",
      "collecting images for drowsy, image number18\n",
      "collecting images for drowsy, image number19\n"
     ]
    }
   ],
   "source": [
    "cap = cv2.VideoCapture(0)\n",
    "\n",
    "#loop through labels\n",
    "for label in labels:\n",
    "    print('collecting images for {}'.format(label))\n",
    "    time.sleep(5)\n",
    "    \n",
    "    #loop through image range\n",
    "    for img_num in range(number_imgs):\n",
    "        print('collecting images for {}, image number{}'.format(label,img_num))\n",
    "        \n",
    "        #webcam feed\n",
    "        ret,frame = cap.read()\n",
    "        \n",
    "        #naming out path\n",
    "        imgname = os.path.join(IMAGES_PATH, label+'.'+str(uuid.uuid1())+'.jpg')\n",
    "        \n",
    "        #writing out image to file\n",
    "        cv2.imwrite(imgname,frame)\n",
    "        \n",
    "        #render to the screen\n",
    "        cv2.imshow('Image collection',frame)\n",
    "        \n",
    "        #2 second delay between captures\n",
    "        time.sleep(2)\n",
    "        \n",
    "        if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "            break\n",
    "\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n",
    "        \n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "8e79408f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/sanjeev/Documents/yolo/yolov5'"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "046fd658",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cloning into 'labelImg'...\n",
      "remote: Enumerating objects: 1986, done.\u001b[K\n",
      "remote: Total 1986 (delta 0), reused 0 (delta 0), pack-reused 1986\u001b[K\n",
      "Receiving objects: 100% (1986/1986), 232.85 MiB | 10.72 MiB/s, done.\n",
      "Resolving deltas: 100% (1187/1187), done.\n"
     ]
    }
   ],
   "source": [
    "!git clone https://github.com/tzutalin/labelImg.git #cloning labelImg for labelling awake and drowsy images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e7c3e0cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pyqt5==5.15.2\n",
      "  Downloading PyQt5-5.15.2-5.15.2-cp35.cp36.cp37.cp38.cp39-abi3-macosx_10_13_intel.whl (47.6 MB)\n",
      "\u001b[K     |████████████████████████████████| 47.6 MB 8.0 MB/s eta 0:00:01     |████████████████████            | 29.6 MB 6.0 MB/s eta 0:00:04��████████████████            | 29.7 MB 6.0 MB/s eta 0:00:03��█████ | 46.0 MB 8.0 MB/s eta 0:00:01\n",
      "\u001b[?25hCollecting lxml\n",
      "  Downloading lxml-4.8.0-cp38-cp38-macosx_10_14_x86_64.whl (4.5 MB)\n",
      "\u001b[K     |████████████████████████████████| 4.5 MB 18.6 MB/s eta 0:00:01\n",
      "\u001b[?25hCollecting PyQt5-sip<13,>=12.8\n",
      "  Downloading PyQt5_sip-12.10.1-cp38-cp38-macosx_10_9_x86_64.whl (83 kB)\n",
      "\u001b[K     |████████████████████████████████| 83 kB 2.9 MB/s  eta 0:00:01\n",
      "\u001b[?25hInstalling collected packages: PyQt5-sip, pyqt5, lxml\n",
      "Successfully installed PyQt5-sip-12.10.1 lxml-4.8.0 pyqt5-5.15.2\n",
      "\u001b[33mWARNING: You are using pip version 20.2.3; however, version 22.0.4 is available.\n",
      "You should consider upgrading via the '/Users/sanjeev/Documents/yolo/yolo/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install pyqt5==5.15.2 lxml #installing requirements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "2b6d9b31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/sanjeev/Documents/yolo'"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "92d59b50",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/sanjeev/Documents/yolo/yolov5\n"
     ]
    }
   ],
   "source": [
    "cd yolov5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "431be260",
   "metadata": {},
   "outputs": [],
   "source": [
    "#training \n",
    "#!python train.py --img 320 --batch 16 --epochs 500 --data dataset.yml --weights yolov5s.pt --workers 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fbdc98f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/sanjeev/Documents/yolo\n"
     ]
    }
   ],
   "source": [
    "cd -"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "581ae54e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/sanjeev/Documents/yolo'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ed32116",
   "metadata": {},
   "source": [
    "# load custom model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "92f4fa2d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://github.com/ultralytics/yolov5/archive/master.zip\" to /Users/sanjeev/.cache/torch/hub/master.zip\n",
      "YOLOv5 🚀 2022-5-13 torch 1.11.0 CPU\n",
      "\n",
      "Fusing layers... \n",
      "Model summary: 213 layers, 7055974 parameters, 0 gradients, 15.9 GFLOPs\n",
      "Adding AutoShape... \n"
     ]
    }
   ],
   "source": [
    "model = torch.hub.load('ultralytics/yolov5', 'custom', path = 'yolov5/runs/train/exp/weights/best.pt',force_reload=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dd711fb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "img = os.path.join('data','images','drowsy.8315e66e-d170-11ec-bff9-1094bbdfb49c.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "801d08d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = model(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "197aa430",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "image 1/1: 720x1280 1 drowsy\n",
      "Speed: 37.3ms pre-process, 307.5ms inference, 1.4ms NMS per image at shape (1, 3, 384, 640)\n"
     ]
    }
   ],
   "source": [
    "results.print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "0e911145",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.imshow(np.squeeze(results.render()))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "989985a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "cap = cv2.VideoCapture(0)\n",
    "while cap.isOpened():\n",
    "    ret,frame = cap.read()\n",
    "    \n",
    "    #make detections\n",
    "    results = model(frame)\n",
    "    \n",
    "    cv2.imshow('YOLO',np.squeeze(results.render()))\n",
    "    \n",
    "    if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1bdac859",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "yolo",
   "language": "python",
   "name": "yolo"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
